Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Imaging Biological Samples with Optical Microscopy01:18

Imaging Biological Samples with Optical Microscopy

9.1K
Optical microscopy uses optic principles to provide detailed images of samples. Antonie van Leeuwenhoek designed the first compound optical microscope in the 17th century to visualize blood cells, bacteria, and yeast cells. In 1830, Joseph Jackson Lister created an essentially modern light microscope. The 20th century saw the development of microscopes with enhanced magnification and resolution.
In optical microscopy, the specimen to be viewed is placed on a glass slide and clipped on the stage...
9.1K
Super-resolution Fluorescence Microscopy01:37

Super-resolution Fluorescence Microscopy

12.3K
Super-resolution fluorescence microscopy (SRFM) provides a better resolution than conventional fluorescence microscopy by reducing the point spread function (PSF). PSF is the light intensity distribution from a point that causes it to appear blurred. Due to PSF, each fluorescing point appears bigger than its actual size, and it is the PSF interference of nearby fluorophores that causes the blurred image. Various approaches to achieving higher resolution through SRFM have recently been...
12.3K
Positron Emission Tomography01:29

Positron Emission Tomography

6.2K
Positron emission tomography (PET) is a medical imaging technique involving radiopharmaceuticals — substances that emit short-lived radiation. Although the first PET scanner was introduced in 1961, it took 15 more years before radiopharmaceuticals were combined with the technique and revolutionized its potential.
One of the main requirements of a PET scan is a positron-emitting radioisotope, which is produced in a cyclotron and then attached to a substance used by the part of the body...
6.2K
Classification of Leukocytes01:30

Classification of Leukocytes

9.0K
Leukocytes are classified into two groups based on the presence or absence of cytoplasmic granules. Granular leukocytes, which contain granules, belong to the myeloid lineage and are divided into three subtypes: neutrophils, eosinophils, and basophils. These cells are roughly spherical and characterized by the granules in their cytoplasm.
Neutrophils are the most abundant type of granular leukocytes, comprising 50-70% of all leukocytes. They feature small, evenly distributed granules and a...
9.0K
Two-Dimensional Microscopy in Microbiology01:29

Two-Dimensional Microscopy in Microbiology

1.8K
Two-dimensional (2D) microscopy encompasses a range of optical techniques that capture images within a single focal plane, offering detailed representations of microscopic structures. These techniques are essential in biological and medical research, enabling the visualization of cellular and subcellular structures with different levels of contrast and specificity.There are several major types of 2D microscopy, each with strengths and applications.Bright-Field MicroscopyBright-field microscopy...
1.8K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Automated biomedical hypothesis generation with time-aware hypergraph contrastive learning.

Knowledge and information systems·2026
Same author

ConceptDrift: leveraging spatial, temporal and semantic evolution of biomedical concepts for hypothesis generation.

Bioinformatics (Oxford, England)·2025
Same author

Boosting Social Determinants of Health Extraction with Semantic Knowledge Augmented Large Language Model.

AMIA ... Annual Symposium proceedings. AMIA Symposium·2025
Same author

Learning to Rank Complex Biomedical Hypotheses for Accelerating Scientific Discovery.

Proceedings. IEEE International Conference on Healthcare Informatics·2025
Same author

Continually-Adaptive Representation Learning Framework for Time-Sensitive Healthcare Applications.

Proceedings of the ... ACM International Conference on Information & Knowledge Management. ACM International Conference on Information and Knowledge Management·2025
Same author

Context-Aware Contrastive Representation Learning for Zero-Shot Biomedical Text Classification.

Proceedings. IEEE International Conference on Bioinformatics and Biomedicine·2025
Same journal

Dynamic GNNs for Precise Seizure Detection and Classification from EEG Data.

Advances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining·2024
Same journal

Using Multimodal Data to Improve Precision of Inpatient Event Timelines.

Advances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining·2024
Same journal

MISNN: Multiple Imputation via Semi-parametric Neural Networks.

Advances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining·2024
Same journal

CrowdTeacher: Robust Co-teaching with Noisy Answers and Sample-Specific Perturbations for Tabular Data.

Advances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining·2021
Same journal

Partitioning-based mechanisms under personalized differential privacy.

Advances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining·2017
查看所有相关文章

相关实验视频

Updated: May 4, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

2.1K

语义知识 增强的超图 对比的表示 学习为零射击生物医学文本分类

Ratri Mukherjee1, Kishlay Jha1

  • 1University of Iowa, Iowa City, Iowa, USA.

Advances in knowledge discovery and data mining : ... Pacific-Asia Conference, PAKDD ..., proceedings. Pacific-Asia Conference on Knowledge Discovery and Data Mining
|December 26, 2025
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的超图方法,用于零射击生物医学文本分类,改进了科学文章的标签与新疾病和药物等未见概念的标签.

关键词:
生物医学多标签文本分类 文本分类相反的学习学习学习.语义上的超图是语义上的超图.零射击学习的学习

更多相关视频

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

983
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.2K

相关实验视频

Last Updated: May 4, 2026

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
07:35

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports

Published on: October 13, 2023

2.1K
Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

983
Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
05:47

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

Published on: June 13, 2025

1.2K

科学领域:

  • 生物医学信息学是生物医学信息学.
  • 自然语言处理自然语言处理.
  • 机器学习 机器学习

背景情况:

  • 零射击生物医学文本分类对于用新概念标记科学文章至关重要.
  • 现有的方法难以捕捉生物医学实体之间的复杂语义关系.
  • 新的疾病,基因和药物不断出现,需要适应性的分类系统.

研究的目的:

  • 开发一种先进的方法,用于零射击生物医学文本分类.
  • 为了有效地利用生物医学实体之间的高阶语义关系.
  • 提高生物医学文本中看不见的标签的概括性能.

主要方法:

  • 提出了一种新的方法,利用超图结构来建模高阶语义关系.
  • 引入了使用生物医学领域知识来生成增强的超图视图的增强策略.
  • 为生物医学实体开发了强大的特征表示.

主要成果:

  • 提出的超图方法显著改善了零射击分类性能.
  • 增强的超图视图增强了模型捕获复杂语义信息的能力.
  • 对大型生物医学体的实验验证实了该方法的有效性.

结论:

  • 基于超图的方法为零射击生物医学文本分类提供了强大的解决方案.
  • 通过超图增强利用语义知识,可以实现更好的概括.
  • 这种方法解决了有效地分类新兴生物医学概念的挑战.